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[#715] fix(mr): The container does not exit because shuffleclient is not closed#882
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LGTM, thanks @zhaobing001 , good catch! merged to master. |
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…not closed (#882) ### What changes were proposed in this pull request? The container does not exit because shuffleclient is not closed ### Why are the changes needed? For #715 1.The process does not exit after the maptask or reducetask execution is complete. The reason is that ShuffleWriteClient has a thread pool that does not close when the task completes. So turning off ShuffleWriteClient can solve this problem. 2.How do I recreate this scene? Initialize a small cluster and submit an mr Task whose requested resources exceed the total resources in the cluster. We can see that all tasks have completed execution without quitting until the timeout time exceeds 60 seconds(mapreduce.task.exit.timeout). The appmaster requests the nodemanager to kill the corresponding container. The nodemanager logs are as follows `2023-03-12 13:56:45,901 INFO [AsyncDispatcher event handler] org.apache.hadoop.mapreduce.v2.app.job.impl.TaskAttemptImpl: Diagnostics report from attempt_1676901654399_1653119_m_000070_0: [2023-03-12 13:56:44.909]Container killed by the ApplicationMaster. [2023-03-12 13:56:44.921]Sent signal OUTPUT_THREAD_DUMP (SIGQUIT) to pid 45556 as user tc_infra for container container_e304_1676901654399_1653119_01_000072, result=success [2023-03-12 13:56:44.985]Container killed on request. Exit code is 143 [2023-03-12 13:56:45.403]Container exited with a non-zero exit code 143. ` ### Does this PR introduce _any_ user-facing change? No. ### How was this patch tested? existing UTs. Co-authored-by: zhaobing <zhaobing@zhihu.com>
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What changes were proposed in this pull request?
The container does not exit because shuffleclient is not closed
Why are the changes needed?
For #715
1.The process does not exit after the maptask or reducetask execution is complete. The reason is that ShuffleWriteClient has a thread pool that does not close when the task completes. So turning off ShuffleWriteClient can solve this problem.
2.How do I recreate this scene?
Initialize a small cluster and submit an mr Task whose requested resources exceed the total resources in the cluster.
We can see that all tasks have completed execution without quitting until the timeout time exceeds 60 seconds(mapreduce.task.exit.timeout). The appmaster requests the nodemanager to kill the corresponding container.
The nodemanager logs are as follows
2023-03-12 13:56:45,901 INFO [AsyncDispatcher event handler] org.apache.hadoop.mapreduce.v2.app.job.impl.TaskAttemptImpl: Diagnostics report from attempt_1676901654399_1653119_m_000070_0: [2023-03-12 13:56:44.909]Container killed by the ApplicationMaster. [2023-03-12 13:56:44.921]Sent signal OUTPUT_THREAD_DUMP (SIGQUIT) to pid 45556 as user tc_infra for container container_e304_1676901654399_1653119_01_000072, result=success [2023-03-12 13:56:44.985]Container killed on request. Exit code is 143 [2023-03-12 13:56:45.403]Container exited with a non-zero exit code 143.Does this PR introduce any user-facing change?
No.
How was this patch tested?
existing UTs.